Dynamics and Moist Thermodynamics of the Boreal Summer Intraseasonal Oscillation

热带的季节内振荡驱动降水周与月的变化和热带气旋的风险。因此，它们对这些地区最重要的天气和气候变化非常重要。北方夏季的季节内振荡可能比我们更熟悉的冬季马登-朱利安振荡更复杂，因为它们不局限于赤道带，它们与海洋和季节平均气候表现出复杂的相互作用，它们涉及广泛的模态和尺度。目前的耦合气候模式不能很好地模拟夏季季节内振荡。pi将分析观测资料，以确定北方夏季季内振荡的详细结构，包括它们的季节变化、时间尺度之间的耦合以及它们与季节变率的相互作用。这些研究将采用最新的卫星遥感数据、地面数据和非常长的降水历史记录。将利用一系列大气-海洋耦合模式以及机械中间模式进行模式研究，以确定驱动BSISO的机制并确定其时间尺度，调查BSISO的可预测性及其与海洋的相互作用，并探索它如何受到厄尔尼诺等季节性异常的影响。这项工作的更广泛影响在于BSISO对热带季节内预报的重要性，对预测洪水和干旱的影响，以及对培养一名博士后和一名研究生的影响。

Intraseasonal oscillations in the tropics drive week-to-week and month-to-month variations in precipitation and in the risk of tropical cyclones. Thus they are important for the most significant weather and climate variations in these regions. Intraseasonal oscillations in the boreal summer are potentially more complex than the more familiar wintertime Madden-Julian oscillation, because they are not confined to the equatorial band, they exhibit complex interactions with the ocean and with the seasonal mean climate, and they involve a wide range of modes and scales. Current coupled climate models do not simulate the summertime intraseasonal oscillations well.The PIs will analyze observations in order to define the detailed structures of the boreal summer intraseasonal oscillations, including their seasonal variations, the coupling between timescales, and their interactions with seasonal variability. These studies will employ newly available remotely sensed data from satellites, ground-based data, and a very long historical record of precipitation. Modeling studies, using a hierarchy of coupled atmosphere-ocean models, as well as mechanistic intermediate models, will be carried out to identify the mechanisms that drive the BSISO and determine its timescales, to investigate the predictability of the BSISO and its interactions with the ocean, and to explore how it is influenced by seasonal anomalies, such as El Nino.Broader impacts of this work are in the importance of the BSISO for intraseasonal forecasting in the tropics, with implications for predicting floods and droughts, and in training a postdoctoral associate and a graduate student.